|
--- |
|
license: mit |
|
base_model: facebook/xlm-v-base |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- massive |
|
metrics: |
|
- accuracy |
|
- f1 |
|
model-index: |
|
- name: scenario-TCR_data-AmazonScience_massive_all_1_1 |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: massive |
|
type: massive |
|
config: all_1.1 |
|
split: validation |
|
args: all_1.1 |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.051647811116576486 |
|
- name: F1 |
|
type: f1 |
|
value: 0.0016647904742274576 |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# scenario-TCR_data-AmazonScience_massive_all_1_1 |
|
|
|
This model is a fine-tuned version of [facebook/xlm-v-base](https://huggingface.co/facebook/xlm-v-base) on the massive dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 3.8189 |
|
- Accuracy: 0.0516 |
|
- F1: 0.0017 |
|
|
|
## Model description |
|
|
|
More information needed |
|
|
|
## Intended uses & limitations |
|
|
|
More information needed |
|
|
|
## Training and evaluation data |
|
|
|
More information needed |
|
|
|
## Training procedure |
|
|
|
### Training hyperparameters |
|
|
|
The following hyperparameters were used during training: |
|
- learning_rate: 5e-05 |
|
- train_batch_size: 32 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 500 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:| |
|
| 3.7541 | 0.27 | 5000 | 3.7437 | 0.0605 | 0.0019 | |
|
| 3.7191 | 0.53 | 10000 | 3.7655 | 0.0620 | 0.0020 | |
|
| 3.7281 | 0.8 | 15000 | 3.8011 | 0.0516 | 0.0017 | |
|
| 3.7116 | 1.07 | 20000 | 3.8592 | 0.0516 | 0.0017 | |
|
| 3.7068 | 1.34 | 25000 | 3.8168 | 0.0516 | 0.0017 | |
|
| 3.7064 | 1.6 | 30000 | 3.8746 | 0.0516 | 0.0017 | |
|
| 3.7059 | 1.87 | 35000 | 3.8189 | 0.0516 | 0.0017 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.33.3 |
|
- Pytorch 2.1.1+cu121 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.13.3 |
|
|
